msc data analytics and finance

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MSc Data Analytics and Finance

Published March 2020 Version 5

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Introduction to the Programme Welcome to the MSc Data Analytics and Finance programme. This handbook provides you with information about the structure of your programme. The programme is made up of the seven core modules listed in the table below. An outline of the content of each of the modules and the assessment methods used can be found in the Module Definition Form section of iLearn.

MSc Data Analytics and Finance Modules

Module Code Module Title Credits Module Type (Core/Option)

DAT7003D Data Design 20 Core

FIN7001D Financial Management 20 Core

DAT7001D Data Handling and Decision Making 20 Core

FIN7002D Reporting Corporate Performance 20 Core

DAT7002D Data Visualisation and Interpretation 20 Core

BUS7012D Business Modelling for Decision Making 20 Core

RES7001D Research Project 60 Core

Please note that modules may not be delivered in this order; please refer to your course timetable. Student Loans Company Funded Students If you have been granted a postgraduate loan from the Student Loans Company, you must progress at an appropriate pace to complete within two years. Arden University is required to make annual reports to the Student Loans Company regarding your progress. If you fall behind, or if you decide you would prefer to study at a slower pace, you may transfer to the Flexible Distance Learning route (see below). However, if you transfer to the more flexible route, you will not be eligible for any continued loan payments from the Student Loans Company. Flexible Distance Learning Students If you have chosen the flexible distance learning route and have not received a postgraduate loan from the Student Loans Company, you have the flexibility to plan your own pace of study. Postgraduate degrees usually take around two to three years to complete depending on how many modules you study each year. In order to achieve this, it is recommended that you aim to complete at least 60 credits each year, equivalent to three 20-credit modules. You will have a maximum of five years to complete the programme (from the date you first started).

Arden University Assessment Regulations Students will be assessed in accordance with the standard Arden University assessment regulations which can be found on the Arden University website http://arden.ac.uk/

http://arden.ac.uk/

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PROGRAMME SPECIFICATION

1. Target Award MSc

2. Programme Title MSc Data Analytics and Finance

3. Exit Awards PGDip Data Analytics and Finance PGCert Data Analytics and Finance PGCert Data Analytics PGCert Finance

4. Programme Leader(s) Mohammed Rehman

5. Delivery Model

Online Blended learning delivery by Arden University staff and supported via the VLE

6. Start date October 2017

7. Programme Accredited by (PSRB or other, if applicable)

8. UCAS Code (If applicable)

9. Relevant QAA subject benchmark statement

QAA General Master’s Degrees (2015), QAA Master’s Degrees in Business and Management (2015)

10. Programme Aims

The aim of the MSc in Data Analytics and Finance is to provide students with core skills and competencies in the area of applied data analytics that they can apply within a financial management environment. The purpose of the programme is enable students to effectively analyse their data needs and to identify and design appropriate methods of gathering data to meet those needs. Students will gain a critical understanding of data handling, using a variety of tools, and how the outcomes of analysis can inform decision making. Finally, students will develop a critical appreciation of the need to effectively communicate the outcomes of analysis via visual methods. The programme will also equip students with higher level financial management skills in financial management to include qualitative and quantitative accounting and management accounting techniques. Students will also have the opportunity to develop a critical understanding of corporate financial reporting and a range of quantitative methods that underpin both financial and business decision making processes. Online teaching materials are derived from established academic research in order to develop critical powers of analysis, reflection and the further development of interpersonal skills in preparation for management roles. Programme participants will build on their previous understanding of data analytics and finance and will have the opportunity to develop new skills which they will be expected to apply within their own working contexts. This is achieved through critical thinking, creativity and personal development. In particular, based upon the established tasks and responsibilities associated with graduates, the purpose of the programme is to enable students to demonstrate the following:

• An ability to critically analyse the need for data gathering for a specific purpose.

• A critical approach to identifying sources of data and designing tools to address specific needs in data gathering

• Well-developed skills in the use of data analytics tools to analyse datasets based upon a stated need

• An ability to evaluate the outcome of analytics activities and make recommendations

• Critically appreciate the role of data visualisation and apply the methods to communicate the outcomes of analytics activities.

• A critical understanding of the implementation an ethical approach to data gathering, analysis and management.

• An ability to select and apply quantitative techniques to support decision making

• An ability to evaluate and apply financial management approaches to management accounting situations

• A critical understanding of corporate financial reporting Arden Values Mapping: the table below identifies how programme outcomes (listed within section 11) meet provide for full coverage of Arden University Values.

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Knowledge & Understanding

Intellectual Thinking

Practical Skills

Transferable Skills

We Support People

B1 D3, D5

We Do the Right Thing

A1 B2

We Innovate

A7 C3, C5

We Take Ownership

A2, A3 B3 D2

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11. Intended programme learning outcomes and the means by which they are achieved and demonstrated

MSc (180 credits)

11a. Knowledge and understanding The means by which these outcomes are achieved The means by which these outcomes are demonstrated

A1 – Critically analyse tools for data gathering and develop innovative and ethical methods of addressing data needs. A2 – Evaluate the role of data handling and decision making within specific contexts A3 – Analyse the need for effective communication of data analytics outcomes with a focus on communicating with non-specialists. A4 – Evaluate quantitative methods that can be applied to aid decision making within financial and business contexts A5 – Evaluate quantitative and qualitative accounting information and use the outcomes to propose solutions to strategic business problems A6 – Critically analyse the role of the finance function and critique key theories related to corporate finance A7 – Undertake self-led research into computing issues in the workplace demonstrating an ethical approach to the application of research principles

Learning and Teaching methods and strategy:

Acquisition of knowledge and understanding (A1 – A7) is

through an integrated learning and teaching pedagogy that

includes both asynchronous and synchronous activity. That

is:

Asynchronous

Independent and directed student study, supported

throughout by comprehensive online multi-media teaching

materials and resources accesses through our VLE

Guided group / project based work

Discussion forums where students discuss and critically

engage with themes emerging from the materials they

engage with, following the posing of questions or

propositions, case studies or similar by either tutor or

students themselves

Podcasts and narrated PowerPoint’s

Synchronous

Online seminars facilitated by VOIP’s where theory and

practice are integrated.

Live chats

Based upon the profile of our typical student body, our

strategy enables students to engage with a variety of

learning tools that best meet their learning styles, overall

objectives and personal circumstances.

Independent study is the cornerstone of the learner

experience supported by engagement with the specialist

tutor and peer engagement.

Knowledge and understanding are assessed through in-module assessments of portfolio submissions, presentations, time-constrained examinations, and report based assignments. Formative assessments are the precursor to the

summative assessments. Appropriate and diverse

formative assessments are provided for students and

are communicated to them via a clear overview to be

found in the assessment brief for each module.

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There is a requirement for written work at all levels

including reports, essays, practical tasks, developed

targeted plans etc., and our formative assessment policy

informs how feedback is supplied by tutors at the draft

assessment phase.

Blended delivery is facilitated by a combination of synchronous face to face classroom based delivery and Asynchronous Independent and directed student study, supported throughout by comprehensive online multi-media teaching materials and resources accessed through our VLE

11b. Intellectual (thinking) skills The means by which these outcomes are achieved The means by which these outcomes are

demonstrated

B1 – Individually and collaboratively analyse

complex problems and requirements and

systematically synthesise and evaluate a range

of potential solutions.

B2 – Demonstrate systematic, ethical and

creative approaches to data gathering, analysis

and communication, showing initiative and

originality.

B3 – Systematically collect and use data from

specific sources to synthesise and evaluate

effective data design, analytics and

communication methods.

B4 – Apply innovative methodologies,

techniques, tools and technologies to

communicate the outcomes of data analysis

based upon a complex problem

Intellectual skills (B1 – B5) are developed throughout the

programme by the methods and strategies outlined in

section A, above.

Specific modules support the development of quantitative

and qualitative analysis, and the development of criticality

and self-reflective skills. In addition, the student’s thinking

skills will be evident in a summative assessment process

which requires and rewards learners for the demonstration

of creative thinking and problem solving, analysis,

judgement and self-reflection in the development of

contextually relevant solutions, and a willingness to explore

and engage with a range of media.

Throughout, the learner is encouraged to develop intellectual skills further by undertaking further independent study and research. Students will be required to demonstrate skill development both individually and collaboratively through the collection of information, analysis and evaluation of findings and presentation of solutions.

Intellectual skills are assessed through a combination of in-course formative exercises and summative assignments, including the submission of portfolios, self-reflective evidence, statistical analyses, qualitative judgements, and research reports/research project.

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B5 – Utilise judgement to draw appropriate

conclusions and make innovative

recommendations.

11c. Practical skills The means by which these outcomes are achieved The means by which these outcomes are

demonstrated

C1 – Effectively design data gathering

techniques to meet a specific need

C2 – Demonstrate data audit and analysis skills

using established tools and techniques

C3 – Effectively communicate the outcomes of

analysis activities using established tools and

techniques in a creative way in order to meet

the needs of the target audience.

C4 – Articulate reasoned evidence to justify

conclusions and recommendations.

C5 – Demonstrate flexibility in adapting to novel

and complex contexts.

C6 – Apply a range of financial and quantitative

methods to drive corporate performance and

decision-making processes

Practical and professional skills are employed in the

production of solutions to real life situations developed

through set briefs, exercises and practical activities. The

important modern-day skills of gathering data, auditing and

analysing datasets and communicating the outcomes to

non-specialists are delivered within this programme

through the completion of practical and analytical

assessments which make thorough use of the student’s

own working context.

Practical skills are further developed and integrated

through a series of in-course online activities and projects

intended to test skills acquired. Group forums provide

opportunities to discuss ideas, progress, the work of others

and the strengths and weakness in the work presented and

particularly support the development of C4. Activities are

provided so that students can work independently to

consolidate their knowledge and grasp of practical skills.

To support the development of practical skills students must supply worked materials and evidence in support of their assignments. Critical reasoning, good presentation and sound evidence trails in all assignments are rewarded. Assessment briefs include a variety of commercial and geographical contextual setting. Students receive feedback on all activities and assignments which includes practical examples for improvement in the application of theory to practice to help them improve both aspects of their skill base.

11c. Transferrable skills The means by which these outcomes are achieved The means by which these outcomes are

demonstrated

D1 – Systematically and competently collate,

synthesise and communicate complex

information effectively

Personal responsibility becomes an increasingly important

skill as students’ progress, culminating in the writing of the

Research project.

As the programme progresses work becomes more

complex and students are tested on their abilities to

To develop transferable skills all assignments must meet time deadlines and word count guidelines. All assessed work must be submitted independently even where group activity has been an element of the process. Students must take responsibility for their own work. All

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D2 – Demonstrate a reflective approach to work

and the capacity to take responsibility for

engaging in self-directed life-long learning for

professional development.

D3 – Work autonomously and collaboratively

demonstrating the highest professional and

ethical standards

D4 – Manage time effectively by learning to plan

and prioritise work in order to meet specified

deadlines.

D5 – Learn independently and collaboratively in

the spirit of critical and self-reflective enquiry.

respond positively to feedback from a variety of audiences,

as well as to manage increasingly large workloads. Students

are required to complete a number of assignments and a

‘research artefact’ that rewards independence originality,

and critical enquiry, and which further enhance

communication and self-reflective skills.

assignments require students to adopt a spirit of critical enquiry and self-reflection which is rewarded in marking guides. These guides are shared with students.

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Exit Awards: Programme Outcome Due to the structure of the proposed programme there are a range of possible exit awards that are dependent upon the module mix achieved by the student. A single Postgraduate Diploma is available which recognises the completion of part 1 of the programme and therefore represents the Data Analytics and Finance route. If a student completes the three Data Analytics modules, then they are able to exit with the Postgraduate Certificate in Data Analytics which is the same award as the target PGCert on offer. If a student completes the three Finance modules, they are able to exit with a Postgraduate Certificate in Finance. If a student achieves a combination of Data Analytics and Finance modules, they are able to exit with a Postgraduate Certificate in Data Analytics and Finance. This approach will enable the student to exit with an award that recognises the elements of the whole programme that they have achieved. Due to the joint nature of the programme, with the “Data Core” cutting across the suite of programmes, it is necessary to closely delineate between what a student has achieved.

Exit Award Knowledge & Understanding

Intellectual Skills Practical Skills Transferrable Skills

Post Graduate Diploma (120 credits)

A1, A2, A3, A4, A5, A6

B1, B2, B3, B4, B5 C1, C2, C3, C4, C5, C6

D1, D2, D3, D4, D5

Post Graduate Certificate (Data Analytics) (60 credits)

A1, A2, A3 B1, B2, B3, B4, B5 C1, C2, C3 D1, D2, D3, D4, D5

Post Graduate Certificate (Finance) (60 credits)

A4, A5, A6 B1, B5 C4, C5, C6 D2, D4, D5

Post Graduate Certificate (Data Analytics and Finance) (60 credits)

A2, A4, A5 B1, B3, B5 C2, C4, C5, C6 D1, D2, D3, D4, D5

12. Graduate Attributes and the means by which they are achieved and demonstrated

Graduate Attributes

The concept of the Arden University Graduate, based upon the definition of ‘graduate attribute’ by Bowden et al

(2000) has been developed around 6 attributes.

Lifelong Learning: Manage employability, utilising the skills of personal development and planning in different

contexts to contribute to society and the workplace.

Reflective Practitioner: Undertake critical analysis and reach reasoned and evidenced decisions, contribute

problem-solving skills to find and innovate in solutions

Professional Skills: Perform effectively within the professional environment. Work within a team, demonstrating

interpersonal skills such as effective listening, negotiating, persuading and presentation. Be flexible and adaptable

to changes within the professional environment

Discipline Expertise: Knowledge and understanding of chosen field. Possess a range of skills to operate within this

sector, have a keen awareness of current developments in working practice being well positioned to respond to

change.

Responsible Global Citizenship: Understand global issues and their place in a globalised economy, ethical

decision-making and accountability. Adopt self-awareness, openness and sensitivity to diversity in culture.

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Effective Communication: Communicate effectively both, verbally and in writing, using a range of media widely

used in relevant professional context. Be IT, digitally and information literate.

The means by which these outcomes are achieved and demonstrated

All six attributes are relevant to this programme, however, five will be developed throughout Level 7 of the MSc

Data Analytics and Finance where they are integrated into all modules and assessed via unit study tasks (individual

and group work) and through summative assessment tasks. Some graduate attributes are assessed in more than

one module allowing for greater development of skills.

Graduate Attribute Mapping

Module Graduate Attribute

Data Design

Lifelong Learning: Manage employability, utilising the skills of personal development and planning in different contexts to contribute to society and the workplace.

Data Handling and Decision Making

Responsible Global Citizenship: Understand global issues and their place in a globalised economy, ethical decision-making and accountability. Adopt self-awareness, openness and sensitivity to diversity in culture.

Data Visualisation and Interpretation

Effective Communication: Communicate effectively both, verbally and in writing, using a range of media widely used in relevant professional context. Be IT, digitally and information literate.

Business Modelling for Decision Making

Professional Skills: Perform effectively within the professional environment. Work within a team, demonstrating interpersonal skills such as effective listening, negotiating, persuading and presentation. Be flexible and adaptable to changes within the professional environment

Financial Management Discipline Expertise: Knowledge and understanding of chosen field. Possess a range of skills to operate within this sector, have a keen awareness of current developments in working practice being well positioned to respond to change.

Reporting Corporate Performance Professional Skills: Perform effectively within the professional environment. Work within a team, demonstrating interpersonal skills such as effective listening, negotiating, persuading and presentation. Be flexible and adaptable to changes within the professional environment

Research Project Discipline Expertise: Knowledge and understanding of chosen field. Possess a range of skills to operate within this sector, have a keen awareness of current developments in working practice being well positioned to respond to change

13. Learning and teaching methods and strategies

Distance Learning Acquisition of all learning outcomes is via engagement with the online module learning material and the online tutoring and programme participant support mechanisms, both of which are delivered via Arden University’s ilearn platform (a Moodle-based system). The learning material comprises purpose-written self-contained lessons with frequent activities and feedback to generate learning and reinforce the knowledge acquisition through frequent application of learning to specific examples. Embedded within the text are links to further reading and appropriate websites. Feedback within the learning material is provided to allow programme participants to check their understanding with that of the tutor. Additionally, group learning activities direct programme participants to the tutor-facilitated discussion forums where they engage in discussion with their peers and receive formative feedback from the module tutor. Each of the 20 credit modules provide programme participants with an understanding of key theoretical and practical management issues, debates and academic informed literatures.

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Teaching/learning methods adopted are transferrable across modules and are similar across modules and include online class discussions, exercises/case studies and group discussions. For each subject being taught a programme of structured online learning activities using both formative and summative assessment is applied. The emphasis is on action learning through the mediation of the module leader for each module. Learning and Teaching activities are: Asynchronous Independent and directed student study, supported throughout by comprehensive online multi-media teaching materials and resources accesses through our Virtual Learning Environment Guided group / project based work Research tasks Discussion forums where students discuss and critically engage with themes emerging from the online materials they engage with, following the posing of questions or propositions, case studies or similar by either tutor or students themselves Podcasts and narrated PowerPoints Synchronous Online seminars facilitated by VOIP’s where theory and practice are integrated Live chats Based upon the profile of our typical student body, our strategy enables students to engage with a variety of learning tools that best meet their learning styles, overall objectives and personal circumstances. Independent study is the cornerstone of the learner experience, supported by subject specialist engagement with the tutor and peer engagement. Blended Learning A strategy which incorporates elements from the above criteria plus the support of face to face input will be utilised. A-synchronous learning will be supported by in class face to face lectures, seminars and workshops. Students will have full access to the ilearn platform and all programme resources within it. Formative opportunities will be available in class and also via ‘Adobe’ hosted seminars. Students will also have access to learning resources at each partner institution. Student leaning will be supported and nurtured at our partner institutions by our tutor team and dedicated centre administrator and on line via our student support team. Summative submissions will all be made via the ‘Turn it In’ platform.

14. Assessment methods and strategies

The assessment process involves both formative and summative elements and is continuing in nature. There will be a focus on encouraging students to apply their knowledge to practical situations. A significant part of this comes from the Research project module. Here students will be required to identify a topic of interest to

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them, which falls within the encompassing field of management. Students will explore this, and will apply their research to the topic, putting forward recommendations which are of practical benefit to the organisation. The approach to coursework assignments will be to encourage students to apply their knowledge to organisations or case study data sets. This could be achieved through the use of case studies but will also involve employees applying information and approaches to their own organisations, or an organisation with which they are familiar. The assessment designed for each module reflects the intentions of that module and will measure the identified learning outcomes. A variety of assessment strategies will be used to reflect and test the achievement of the learning outcomes. These are detailed within each module and mapped in the table below. Assessment questions and cases are seen to be dynamic and are reviewed quarterly in order to maintain rigour and reflect changes in professional focus and practice. There is a requirement for written work at all levels including reports, essays, developed plans, portfolios of work etc. and our assessment policy informs how feedback is supplied by tutors at the formative and summative assessment stage. Critical analysis is encouraged at all levels culminating in a Research Project.

15. Employability

Entrants to this programme are highly likely to be in work, (be it Full or part Time). The MSc in Data Analytics and Finance is designed to offer the degree of flexibility required to ensure that even those employed in full time positions have the maximum opportunity to fulfil their programme of study. The programme aims to develop skills and knowledge such that graduates can confidently enter the computing management environment or can improve their existing career prospects within it. This degree develops a range of transferrable skills and provides opportunities for these to be evidenced. In particular, the final research project provides the ability to demonstrate higher level academic skills. The programme has been specifically designed to provide career development in a rapidly developing and business critical area and will be marketed as such. The vast majority of students are likely to be employed in the business function related to their chosen pathway and the courses will enable appropriate progression. However, it is noted that the distributed nature of Arden University students makes conventional careers support difficult for those who choose to study the programme and are not employed. The use of the ‘Abintegro provider’ allows us to offer a range of support in career development and there are opportunities for students to purchase more specialist support if required. The addition of imbedded graduate attributes adds value to the qualification in terms of providing ‘industry ready’

graduating students.

16. Entry Requirements

Arden University is keen to ensure that the programme is available to all those who can benefit from it. Normally entry is via: A degree equivalent to UK second class honours standard, English ability equivalent to IELTS 6.5 (no less than 6.0 in any element), where the medium of undergraduate study was not English; Applicants with existing postgraduate computing management awards may be eligible for entry with advanced standing and will be considered through the APL process. Applicants who have substantial relevant experience (typically 5 years) and are able to demonstrate via references

and supporting curriculum vitae an ability to successfully complete the programme may be admitted where they

do not possess degree equivalent qualifications. It is not intended to offer exemptions based on experiential

learning.

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17. Programme Structure

MSc Data Analytics and Finance

Module Code Module Title Credits

Module Type (Core/Option)

Assessment Method

DAT7003 Data Design 20 Core Assignment Assignment

DAT7001 Data Handling and Decision Making 20 Core Assignment

DAT7002 Data Visualisation and Interpretation

20 Core Presentation

BUS7012 Business Modelling for Decision Makers

20 Core Time-Constrained Assignment Assignment

FIN7001 Financial Management 20 Core Assignment

FIN7002 Reporting Corporate Performance 20 Core Assignment

RES7001 Research Project 60 Core Research Proposal & Dissertation or Journal Formatted Article & Viva

18. Subject: I260 (Data Management),

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Mapping of Intended Programme Learning Outcomes and Modules MSc Data Analytics and Finance

Programme

Learning Outcomes

Modules

Mo

du

le T

ype

(Co

mp

uls

ory

(C

) o

r O

pti

on

(O

)A

1

A2

A3

A4

A5

A6

A7

B1

B2

B3

B4

B5

C1

C2

C3

C4

C5

C6

D1

D2

D3

D4

D5

Leve

l 7

Data Design C X X X X X X X X X X X X

Data Handling and Decision

Making C X X X X X

X X X X X X X

Data Visualisation and

Interpretation C X X X X X

X X X X X X X

Business Modelling for

Decision Makers C

X X X

X X X X X X

Financial Management C X X X X X X X X X

Reporting Corporate

Performance C

X X X

X X X X X X

Research Project C X X X X X X X X X X X X

JSOJ151220

msc data analytics and finance

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